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Abstract

Social networks recently came under severe criticism for easy-going handling of user data. Millions of users voluntarily release private and business data without considering potential impacts on their real life that may come along with that. Used for personalized advertising or attendee profiling, user data are of utmost importance for economic success of the maintaining network. Hence, platform providers exploit all promising options to gather data while privacy and data security seem partially to be a pain for them. Dozens of security lacks and data thefts have emerged for almost every available platform. In addition, techniques and methods exist to secretly gather more user data, e.g., by proper fusion of miscellaneous information, analysis of visited websites, or social games. Even worse, misuse or rather sale of user data might be part of the marketing concept. This chapter analyzes the business networks LinkedIn and Xing, and the more leisure time related social communities Facebook and StudiVZ. In particular, differences in collecting and handling of user data are of interest. Based on that, we present and analyze reported criticism based on published and on own investigated data. Then we evaluate whether that criticism is justified, hypercritical, or understatement. On behalf of analyzing potential threats and pitfalls, we finally work out existing and potential privacy risks as well as resulting consequences for the real life of community members.

Introduction

Online social networking is an ever-growing market where the big players already earn several million dollars per year (Schwartz, J., 2008). That regards both, business networks like LinkedIn and Xing, as well as rather leisure time related social communities like Facebook and StudiVZ. These online networks are part of the so-called “Web 2.0” and social software. Social software provides ease of use for online information-, identity- and relation-management (Schmidt, 2006). Instead of pure information retrieval, the users generate and administrate online content on a platform provided. The platform mainly handles the necessary technical and organizational challenges. Social networks are a special type of those platforms supporting people with features for online interaction. Therefore the platform user establishes a mostly self-designed profile reflecting the user’s online identity. Based on that, the user connects to other user profiles. Finally, the social network builds a graph, usually called “social graph”, where user profiles represent the nodes and links represent the edges respectively (Wasserman, S. & Faust, K., 1994). The main functionalities of social networks are based on this graph, e.g., search engine and message services. According to a representative online survey, 63% of the people in Germany using the Internet are already members of at least one social network (ForschungsWerk GmbH, 2009). Within the group of 18 to 29 year old people, more than 90% are members of social networks. Nearly half of the users with profiles in Facebook or StudiVZ login to the community almost every day. Anyway, social networks still register an increasing number of users and daily logins.

This chapter explores two types of social networks, i.e., business networks and more privately-used social communities. Business networks allow people to introduce themselves, to connect to business contacts as well as to search for joboffers. Companies, headhunters or profiling experts use these platforms to search for suitable employees, too. Profiling services are usually offered by the platform provider or affiliated companies. Social communities provide similar features as business networks but are applied in a more private context. Here users are primarily interested in staying or getting in contact with friends, in common online activities such as games or chats, in sharing of online photo albums, etc. Often there are smooth transitions between several profiles spanned over different networks. These profiles may be linked by consistent identifiers like the real name, date of birth or email address for example. Hence, detailed personal profiles including both business and private user data could possibly be created. Thus, if both types of social networks are used simultaneously, a clear partition of privately-assigned and business-related user data becomes very difficult. To circumvent uncontrolled access to user data, the platforms usually allow differentiating type and purpose of access to user data by protective mechanisms.

Besides different scopes of business, considered networks significantly differ in size, number of users, options for personal representation and first of all, in the way of protecting private user data. Private data are of important value for social network owners since these can be used (or sold respectively) for advertising or better and highly profitable, personalized advertising. The latter seems to provide market sizes of several billion dollars per year and hence, is of enormous interest for platform providers. Only a huge number of users and a maximum of personal user data assure attractiveness and economical success of the platform. Consequently, priority objective of platform providers is collection of as much user data as possible.

Alongside the rise of social networks, large parts of human life and social interactions migrated into the Internet. A vast amount of private and business data has been put into and stored in these networks. Communities, like StudiVZ in this example, directly invite people to “find friends, send messages to and chat with friends as well as to comment on and link other users or content … and gruscheln of course!” (StudiVZ about, 2010) Note, similar to the “poke” option at Facebook, “gruscheln” is a neologism of StudiVZ denoting a mix of greeting and snuggling (German: kuscheln).